Population exposure-efficacy and exposure-safety analyses for rucaparib in patients with recurrent ovarian carcinoma from Study 10 and ARIEL2
Bibliographic record
Abstract
Objective To evaluate correlations between rucaparib exposure and selected efficacy and safety endpoints in patients with recurrent ovarian carcinoma using pooled data from Study 10 and ARIEL2. Methods Efficacy analyses were limited to patients with carcinomas harboring a deleterious BRCA1 or BRCA2 mutation who had received ≥2 prior lines of chemotherapy. Safety was evaluated in all patients who received ≥1 rucaparib dose. Steady-state daily area under the concentration-time curve (AUC ss ) and maximum concentration (C max,ss ) for rucaparib were calculated for each patient and averaged by actual dose received over time (AUC avg,ss and C max,avg,ss ) using a previously developed population pharmacokinetic model. Results Rucaparib exposure was dose-proportional and not associated with baseline patient weight. In the exposure-efficacy analyses ( n = 121), AUC avg,ss was positively associated with independent radiology review-assessed RECIST response in the subgroup of patients with platinum-sensitive recurrent disease ( n = 75, p = 0.017). In the exposure-safety analyses ( n = 393, 40 mg once daily to 840 mg twice daily [BID] starting doses), most patients received a 600 mg BID rucaparib starting dose, with 27% and 21% receiving 1 or ≥2 dose reductions, respectively. C max,ss was significantly correlated with grade ≥2 serum creatinine increase, grade ≥3 alanine transaminase/aspartate transaminase increase, platelet decrease, fatigue/asthenia, and maximal hemoglobin decrease ( p < 0.05). Conclusion The exposure-response analyses provide support for the approved starting dose of rucaparib 600 mg BID for maximum clinical benefit with subsequent dose modification only following the occurrence of a treatment-emergent adverse event in patients with BRCA -mutated recurrent ovarian carcinoma.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.010 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.006 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".